Triple
T11411223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 389 cu in Pontiac V8 |
E270375
|
entity |
| Predicate | compressionRatioRange |
P12420
|
FINISHED |
| Object | 8.6:1 to 10.75:1 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 8.6:1 to 10.75:1 | Statement: [389 cu in Pontiac V8, compressionRatioRange, 8.6:1 to 10.75:1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compressionRatioRange Context triple: [389 cu in Pontiac V8, compressionRatioRange, 8.6:1 to 10.75:1]
-
A.
compressionRatio
chosen
Indicates the proportional reduction in size or volume achieved when something is compressed compared to its original size.
-
B.
compressionType
Indicates the method or format used to compress data or content in the relationship.
-
C.
compressionGoal
Indicates the target level or outcome of data size reduction that a compression process aims to achieve.
-
D.
compressionScope
Indicates the extent or range within which compression is applied to data or content.
-
E.
pegRatio
Indicates the relationship between a company’s price-to-earnings (P/E) ratio and its expected earnings growth rate, expressing how highly the market values each unit of anticipated growth.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8015017d08190b4020c76545556d6 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e70ffd708190b62a78ebcbce9f78 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.